The compounding of polyvinyl chloride (PVC) with two types of fillers and some additives were studied for the manufacturing of acid resistant tile. Various concentrations of two types of fillers namely; calcium carbonate and recycled glass powder were used along with different additives generally categorized as plasticizers, stabilizers, and lubricants were mixed in the standard concentration unit parts per hundred resins (phr) with the PVC as base polymer. The effects of filler materials on acid resistant towered different acids like sulphuric, nitric and hydrochloric at different concentration were studied. Samples which passed the test were further checked for dielectric strength and mechanical properties. It was found that the recycl

This research aims to investigate the effect of four types of nanomaterial on the Marshall properties and durability of warm mix asphalt (WMA). These types are; nano silica(NS), nano carbonate calcium (NCC), nano clay(NC), and nanoplatelets (NP). For each type of Nanomaterial, three contents are tried as following; NS(1%, 3%, and 5%), NCC(2%, 4%, and 6%), NC(3%, 5%, and 7%), and NP (2%, 4%, and 6%) by weight of asphalt cement. Following Marhsall mix design method, the optimum asphalt cement content is determined, thereafter the optimum dosage for each nanomaterial is obtained based on the highest Marshall stability value. The durability of the control mix (no nanomaterial) and modified mixtures have been compared based on moisture damage, r

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

The study aimed to analyze the effect of meteorological factors (rainfall rate and temperature) on the change in land use in the marshes of the Al‐Majar Al‐Kabir region in southern Iraq. Satellite images from Landsat 7 for 2012 and Landsat 8 for 2022 were used to monitor changes in the land coverings, the images taken from the Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors of the Landsat satellite. Geometric correction was used to convert images into a format with precise geographic coordinates using ArcMap 10.5. The maximum likelihood classification method was used to examine satellite image data using a supervised approach, and the data were analyzed statistically. We obtained clear images of the area,

The specifications of lubricating oil are fundamentally the final product of materials that have been added for producing the desired properties. In this research, spherical nanoparticles copper oxide (CuO) and titanium oxides (TiO₂) are added to SAE 15W40 engine oil to study the thermal conductivity, stability, viscosity of nano-lubricants, which are prepared at different concentrations of 0.1%, 0.2%, 0.5%, and 1% by weight, and also their pour point, and flash point as five quality parameters. The obtained results show that CuO nanoparticles in all cases, give the best functionality and effect on engine oil with respect to TiO₂. With 0.1 wt. % concentration, the thermal conductivity of CuO/oil and TiO₂/

The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company

Permanent deformation (rutting) of asphalt mixtures is one of the major forms of distress. Aggregate gradation is one of the most important factors affecting the permanent deformation of asphalt mixtures. Other variables are also important to understand their effects on the mixture such as temperature, binder content and compaction level. For this purpose 6 different aggregate gradations have been chosen and each one of them has been manufactured / tested with different variables. The results showed that at relatively low temperature there is little effect of aggregate packing on the permanent deformation. However, as the temperature increases the effect of gradation becomes apparent, in that the better the packing the better the resistance

In architectural learning, it is difficult to stimulate cultural awareness through the traditional education approaches, which results in historic places being neglected as knowledge sources. This research explores the premise that sketch-based visual storytelling may act as a generative approach to connect cognition, emotion, and behavior in historical contexts. The study adopts a qualitative methodology to explore a learning experience comprising two phases: the first is a formal educational setting, and the second is a historical and cultural context, aiming to investigate the role of sketch-based storytelling in enhancing cultural awareness. MAXQDA was employed to code the students’ storyboards on three levels of cultural awareness, m

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c